Artificial intelligence chatbots in language learning for disadvantaged populations (migrants and aboriginal). State of the art and challenge

Abstract

The length will be 250 to 300 words in English. The latest United Nations reports reveal profound global disparities in educational outcomes and societal impacts stemming from internet accessibility. In Australia and the Caribbean, First Nations communities are the most marginalized due to the lasting effects of colonialism, leading to a significant digital divide. Conversely, in Spain—and typical of many European nations—it is the immigrant population that encounters the greatest obstacles to educational access. This study seeks to explore the impact of internet availability and chatbots on language learning among disadvantaged populations engaged in Early and Primary Language Education across these three regions since education is pivotal for fostering inclusion, promoting social mobility, and ensuring the flourishing of these communities. A systematic review of scientific literature indexed in Web of Science, SCOPUS, and DIALNET was undertaken, focusing on publications relevant to the study. The research methodology involved using two Boolean factors related to the focus of the study. Findings indicate a scarcity of research on chatbots in language education for disadvantaged populations, despite their prevalence in general education studies with chatbots or chatbot for languages learning. The study advocates for integrating AI and chatbots as a catalyst for enhancing language skills among vulnerable most young learners in the school. The goal is to address a two-fold challenge: to advance systematic research in the field of inclusive language learning and to raise awareness of chatbots’ potential in achieving the UN’s Sustainable Development Goal 4 outlined in the UN's 2030 Agenda: equitable and quality education for all.